Integration Developer (Multi-Cloud – AWS / Azure / GCP)

Job Description

Company Overview

Rhythm Innovations is an innovative startup specializing in fleet risk management. We are committed to driving customer delight through innovative solutions and a customer-centric approach. As we continue to grow.

Position Overview

We are seeking a highly skilled Integration Developer to design, build, and maintain cloud-native, API-led integration solutions. This role is cloud-agnostic: strong hands-on expertise with AWS is required, and experience building equivalent solutions on Azure or Google Cloud Platform (GCP) is equally valued. In this role, you will serve as a technical leader responsible for developing scalable data pipelines, serverless applications, and enterprise integration patterns that connect internal systems, third-party platforms, and data sources across the organization.

You will work at the intersection of application development, data engineering, and cloud architecture, applying API-led connectivity principles and leveraging core cloud services for compute, storage, ETL/ELT, and relational data - for example AWS Lambda / S3 / Glue / RDS, Azure Functions / Blob Storage / Data Factory / Azure SQL, or GCP Cloud Functions / Cloud Storage / Dataflow / Cloud SQL - to deliver robust solutions that drive business value.

Requirements

Key Responsibilities

• Define and document end-to-end integration architectures, including data flows, API contracts, event-driven patterns, and ETL/ELT pipelines using cloud-native services (AWS, Azure, or GCP).

• Design and build API-led integrations following layered API principles (experience, process, and system APIs), with strong command of REST, and working knowledge of GraphQL and/or gRPC where appropriate.

• Evaluate, recommend, and implement integration patterns (pub/sub, request-reply, choreography, orchestration) that align with organizational scalability and reliability goals, independent of the underlying cloud provider.

• Establish architectural standards, design blueprints, and reusable templates for integration workloads across multiple business domains and cloud platforms.

• Design and develop serverless functions in Python , Node.js to power real-time integrations, event processing, and microservice orchestration (e.g., AWS Lambda, Azure Functions, or GCP Cloud Functions/Cloud Run).

• Implement workflow orchestration for complex, multi-step business processes and error-handling strategies (e.g., AWS Step Functions, Azure Logic Apps/Durable Functions, or GCP Workflows).

• Optimize cold-start performance, memory allocation, concurrency controls, and cost efficiency across serverless workloads.

• Architect data lake and data staging solutions on cloud object storage (e.g., Amazon S3, Azure Blob Storage, or Google Cloud Storage), defining bucket/container strategies, lifecycle policies, versioning, encryption, and access controls.

• Design and manage relational database instances (PostgreSQL, MySQL, or Aurora on AWS; Azure SQL/Postgres/MySQL; or Cloud SQL/AlloyDB on GCP), including schema design, indexing strategies, read replicas, and automated failover configurations.

• Implement secure, performant data access patterns between storage, databases, and downstream API consumers using private networking (VPC/VNet), IAM/role-based access, and encryption at rest and in transit.

• Build and maintain ETL/ELT jobs (e.g., AWS Glue/PySpark, Azure Data Factory/Synapse pipelines, or GCP Dataflow/Dataproc) to transform, enrich, and load data across structured and semi-structured sources.

• Manage and optimize data cataloging, crawlers/classifiers, and partition strategies for efficient data discovery and query performance.

• Design workflows and triggers for orchestrating complex, dependency-aware data pipelines with built-in monitoring and alerting.

• Implement infrastructure-as-code (IaC) using Terraform, or cloud-native tooling (AWS CloudFormation/CDK, Azure Bicep/ARM, or GCP Deployment Manager) to provision and manage integration infrastructure reproducibly.

• Build and maintain CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, GitLab CI, AWS CodePipeline/CodeBuild, or Google Cloud Build) for automated testing, deployment, and rollback of integration workloads.

• Establish comprehensive observability using native or third-party tooling (e.g., CloudWatch/X-Ray, Azure Monitor/Application Insights, Google Cloud Operations Suite) to monitor latency, error rates, throughput, and cost metrics.

Key Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field (or equivalent practical experience).

• 5+ years of professional experience in software development, with at least 3 years focused on integration architecture and cloud-native development.

• Deep, hands-on expertise with at least one major cloud platform (AWS, Azure, or GCP) across compute, storage, ETL, and relational database services in production environments at scale; multi-cloud experience is a strong plus.

• Solid knowledge of APIs and API-led integration approaches — API design and versioning, API gateways, authentication/authorization (OAuth2, JWT), rate limiting, and API lifecycle management.

• Strong proficiency in at least one of Python, Node.js (TypeScript), or Java, with experience writing production-grade, testable code.

• Demonstrated experience designing RESTful APIs, event-driven architectures, and ETL/ELT data pipelines.

• Working knowledge of infrastructure-as-code tools (Terraform preferred, or a cloud-native equivalent) and CI/CD automation.

• Solid understanding of relational database design, SQL optimization, and data modeling best practices.

• Excellent communication skills with the ability to convey complex technical concepts to both technical and non-technical stakeholders.

• A professional cloud architecture or developer certification on AWS, Azure, or GCP (e.g., AWS Solutions Architect – Professional, Azure Solutions Architect Expert, or Google Professional Cloud Architect), or equivalent demonstrable expertise.

• Experience with additional managed services for messaging, streaming, or eventing (e.g., EventBridge/SQS/SNS/Kinesis on AWS; Service Bus/Event Grid/Event Hubs on Azure; Pub/Sub on GCP).

• Familiarity with data governance frameworks, data quality tooling, and compliance standards (GDPR, HIPAA, SOC 2).

• Prior experience in enterprise integration platforms (MuleSoft, Informatica, Talend, Boomi, or Apigee) and/or experience migrating or extending such workloads onto cloud-native services.

• Exposure to containerized workloads (e.g., ECS/Fargate/EKS, Azure Container Apps/AKS, or GCP Cloud Run/GKE) and hybrid or multi-cloud architectures.

• Experience with Apache Spark, Apache Kafka, or real-time streaming architectures.

Benefits

What We Offer

• Opportunity to define and lead integration architecture at a growing startup.

• Collaborative and dynamic work environment.

• Professional growth and development opportunities.

Requirements
Key Responsibilities • Define and document end-to-end integration architectures, including data flows, API contracts, event-driven patterns, and ETL/ELT pipelines using cloud-native services (AWS, Azure, or GCP). • Design and build API-led integrations following layered API principles (experience, process, and system APIs), with strong command of REST, and working knowledge of GraphQL and/or gRPC where appropriate. • Evaluate, recommend, and implement integration patterns (pub/sub, request-reply, choreography, orchestration) that align with organizational scalability and reliability goals, independent of the underlying cloud provider. • Establish architectural standards, design blueprints, and reusable templates for integration workloads across multiple business domains and cloud platforms. • Design and develop serverless functions in Python , Node.js to power real-time integrations, event processing, and microservice orchestration (e.g., AWS Lambda, Azure Functions, or GCP Cloud Functions/Cloud Run). • Implement workflow orchestration for complex, multi-step business processes and error-handling strategies (e.g., AWS Step Functions, Azure Logic Apps/Durable Functions, or GCP Workflows). • Optimize cold-start performance, memory allocation, concurrency controls, and cost efficiency across serverless workloads. • Architect data lake and data staging solutions on cloud object storage (e.g., Amazon S3, Azure Blob Storage, or Google Cloud Storage), defining bucket/container strategies, lifecycle policies, versioning, encryption, and access controls. • Design and manage relational database instances (PostgreSQL, MySQL, or Aurora on AWS; Azure SQL/Postgres/MySQL; or Cloud SQL/AlloyDB on GCP), including schema design, indexing strategies, read replicas, and automated failover configurations. • Implement secure, performant data access patterns between storage, databases, and downstream API consumers using private networking (VPC/VNet), IAM/role-based access, and encryption at rest and in transit. • Build and maintain ETL/ELT jobs (e.g., AWS Glue/PySpark, Azure Data Factory/Synapse pipelines, or GCP Dataflow/Dataproc) to transform, enrich, and load data across structured and semi-structured sources. • Manage and optimize data cataloging, crawlers/classifiers, and partition strategies for efficient data discovery and query performance. • Design workflows and triggers for orchestrating complex, dependency-aware data pipelines with built-in monitoring and alerting. • Implement infrastructure-as-code (IaC) using Terraform, or cloud-native tooling (AWS CloudFormation/CDK, Azure Bicep/ARM, or GCP Deployment Manager) to provision and manage integration infrastructure reproducibly. • Build and maintain CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, GitLab CI, AWS CodePipeline/CodeBuild, or Google Cloud Build) for automated testing, deployment, and rollback of integration workloads. • Establish comprehensive observability using native or third-party tooling (e.g., CloudWatch/X-Ray, Azure Monitor/Application Insights, Google Cloud Operations Suite) to monitor latency, error rates, throughput, and cost metrics.